UD_Telugu_English-TECT
Treebank card from UD release 2.18: metadata and texts come from UD_Telugu_English-TECT/README.md; size is counted by streaming the .conllu files and checked against the release stats.xml. Generated by tools/treebanks build; do not edit by hand. Papers: Papers: UD_Telugu_English-TECT; seeds: seeds/; converter: convert.md.
| Field | Value |
|---|---|
| UD name | UD_Telugu_English-TECT |
| Language | Telugu English (qte) |
| Family | Code switching |
| Treebank code | qte_tect |
| UD page | universaldependencies.org/treebanks/qte tect/index.html |
| License | CC BY-SA 4.0 |
| Genres | spoken |
| Text in data | yes |
| Parallel | no |
| In UD since | UD v2.14 |
| Authors | Anishka Vissamsetty |
| Contact | anishka18v@gmail.com |
| Development | in the UD repo (here) |
Annotation layers
| Layer | Origin |
|---|---|
| Lemmas | automatic |
| UPOS | converted with corrections |
| XPOS | not available |
| Features | not available |
| Relations | automatic |
UD scale: manual native — annotated by hand directly in UD; converted from manual — converted from manual annotation in another scheme; converted with corrections — converted and partly corrected by hand; automatic with corrections — automatic, with partial manual corrections; automatic — automatic; not available — the layer is absent.
Size
| Split | Sentences | Tokens | Words | Multiword tokens | Empty nodes |
|---|---|---|---|---|---|
| train | 61 | 290 | 290 | 0 | 0 |
| test | 36 | 166 | 166 | 0 | 0 |
| total | 97 | 456 | 456 | 0 | 0 |
Tokens are surface tokens (Spanish vámonos is one), words are syntactic words (vamos + nos); multiword tokens are those split into several words; empty nodes are the N.M nodes of the enhanced graph. Splits dev are absent from the release.
Summary
UD Telugu_English-TECT is a Telugu-English code-switching treebank.
Introduction
The treebank consists of edited data from the Telugu UD treebank (Rama and Vajilla, 2021), sentences from a grammar book, and the MASSIVE dataset, spoken conversational utterances in Telugu (FitzGerald et al., 2022; Bastianelli et al., 2020). The sentences were randomly selected from each corpus. The sentences were romanized and each sentence was altered to contain at least one code-switch. The sentences were then annotated following the Universal Dependencies annotation scheme.
This page in Markdown → https://md.mova.elamur.ai/free/en/docs/treebanks/qte/tect/